Improved Energy Detection Spectrum Sensing Method for OFDM-Based Cognitive Radio System

  • Min Jia
  • Hao Yang
  • Xuemai Gu
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 202)


The spectrum sensing scheme which is used for detecting primary users in a licensed spectrum are essential to utilize the spectrum effectively for cognitive radio communication systems. As a matter of fact, sensing accuracy is regarded as the most important factor for spectrum sensing with the intension of sufficient protection for the primary user. A novel spectrum sensing scheme which exploits the cyclic prefix of an orthogonal frequency-division multiplexing (OFDM) symbol as well as idle period containing no information symbols is proposed in this chapter. From the analysis and simulation results, it shows that the proposed scheme can improve sensing accuracy and increase system throughput compared with the conventional scheme which uses only idle period.


OFDM Cognitive radio Cyclic prefix Energy detection 



This work is supported by the Fundamental Research Funds for the Central Universities (Grant No. HIT. NSRIF. 2010091), the National Natural Science Foundation of China (Grant No. 61201143), the National Science Foundation for Post-doctoral Scientists of China (Grant No. 2012 M510956), and the Post-doctoral Funds of Heilongjiang Province (Grant No. LBHZ11128).


  1. 1.
    Mitola J, Maguire GQ (1999) Cognitive radio: making software radios more personal. IEEE Pers Comm 6(4):13–18CrossRefGoogle Scholar
  2. 2.
    Zengyou Sun, Qianchun Wang, Chenghua Che (2010) Study of cognitive radio spectrum detection in OFDM system. In: Proceedings of the 2010 Asia-Pacific conference on wearable computing systems, Shenzhen, pp 235–238Google Scholar
  3. 3.
    Refik Fatih USTOK (2010) Spectrum sensing techniques for cognitive radio systems with multiple aneennas. June 2010.
  4. 4.
    Anand Chandran, Anantha Karthik.R (2010) Evaluation of energy detector based spectrum sensing for OFDM based cognitive radio. In: Proceedings of the international conference on communication and computational intelligence—2010, Kongu Engineering College, Perundurai, Erode, 27–29 Dec 2010, pp 163–167Google Scholar
  5. 5.
    Jianping An (2010) Spectrum sensing for OFDM systems based on cyclostationary statistical test. In: Proceedings of the 2010 6th international conference on wireless communications networking and mobile computing (WiCOM), Chengdu, 23–25 Sept 2010, pp 1–4Google Scholar
  6. 6.
    Van Trees HL (2007) Detection, estimation, and linear modulation theory. Publishing House of Electronics Industry, Beijing, pp 187–286Google Scholar
  7. 7.
    Khambekar N, Dong L, Chaudhary V (2007) Utilizing OFDM guard interval for spectrum sensing. In: Proceedings of the IEEE wireless communications and networking conference, Hong Kong, Mar 2007, pp 38–42Google Scholar
  8. 8.
    Dong Chunli, Yang Zhen, Zhang Hui, Tian Feng (2010) Research of spectrum holes detection algorithms for cognitive radio. In proceedings of the 2010 12th IEEE international conference on communication technology (ICCT), Nanjing, 11–14 Nov 2010, pp 1449–1452Google Scholar

Copyright information

© Springer Science+Business Media New York 2012

Authors and Affiliations

  1. 1.Communication Research Center, School of Electronics and Information EngineeringHarbin Institute of TechnologyHarbinChina

Personalised recommendations